• DocumentCode
    2559798
  • Title

    Unscented Particle Filter algorithm based on artificial fish swarm algorithm

  • Author

    Tian, Yu-min ; Chen, Li

  • Author_Institution
    Res. Inst. of Comput. Peripherals, Xidian Univ., Xi´´an, China
  • fYear
    2012
  • fDate
    29-31 May 2012
  • Firstpage
    1123
  • Lastpage
    1126
  • Abstract
    Aiming at the problem of Unscented Particle Filter (UPF) algorithm such as particles degeneracy and particles impoverishment, by use of the behaviors of preying, swarming and following in the artificial fish swarm algorithm, an artificial fish swarm algorithm is used to make the particles of UKF move toward the global optimum, which optimalizes the resampling process and relieves the problem of particles degeneracy and impoverishment. Experiments show that this algorithm improves the estimation accuracy of UPF algorithm.
  • Keywords
    Kalman filters; particle filtering (numerical methods); particle swarm optimisation; UKF; artificial fish swarm algorithm; particles degeneracy; particles impoverishment; preying behavior; resampling process optimisation; swarming behavior; unscented Kalman filter; unscented particle filter algorithm; Algorithm design and analysis; Fellows; Filtering algorithms; Marine animals; Particle filters; Signal processing algorithms; Artificial Fish Swarm Algorithm; Unscented Particle Filter; particles impoverishment; resampling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2012 Eighth International Conference on
  • Conference_Location
    Chongqing
  • ISSN
    2157-9555
  • Print_ISBN
    978-1-4577-2130-4
  • Type

    conf

  • DOI
    10.1109/ICNC.2012.6234707
  • Filename
    6234707